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ASGR: An Artificial Spider-Web-Based Geographic Routing in Heterogeneous Vehicular Networks

Chen, C and Liu, L and Qiu, T and Yang, K and Gong, F and Song, H (2019) 'ASGR: An Artificial Spider-Web-Based Geographic Routing in Heterogeneous Vehicular Networks.' IEEE Transactions on Intelligent Transportation Systems, 20 (5). 1604 - 1620. ISSN 1524-9050

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Abstract

Recently, vehicular ad hoc networks (VANETs) have been attracting significant attention for their potential for guaranteeing road safety and improving traffic comfort. Due to high mobility and frequent link disconnections, it becomes quite challenging to establish a reliable route for delivering packets in VANETs. To deal with these challenges, an artificial spider geographic routing in urban VAENTs (ASGR) is proposed in this paper. First, from the point of bionic view, we construct the spider web based on the network topology to initially select the feasible paths to the destination using artificial spiders. Next, the connection-quality model and transmission-latency model are established to generate the routing selection metric to choose the best route from all the feasible paths. At last, a selective forwarding scheme is presented to effectively forward the packets in the selected route, by taking into account the nodal movement and signal propagation characteristics. Finally, we implement our protocol on NS2 with different complexity maps and simulation parameters. Numerical results demonstrate that, compared with the existing schemes, when the packets generate speed, the number of vehicles and number of connections are varying, our proposed ASGR still performs best in terms of packet delivery ratio and average transmission delay with an up to 15% and 94% improvement, respectively.

Item Type: Article
Uncontrolled Keywords: Delays, Network topology, Roads, Routing, Routing protocols, Vehicular ad hoc networks, Vehicular ad hoc networks, artificial spider-web, connection quality, latency model, routing protocol, selective forwarding.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 23 May 2018 13:38
Last Modified: 15 May 2020 18:15
URI: http://repository.essex.ac.uk/id/eprint/22099

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